ACID at Scale: Why MySQL Needs a Distributed SQL Alternative

MySQL’s simplicity and robust single-instance ACID guarantees have made it a developer favorite for years. The familiar ease of use, quick installation, and a rich ecosystem contribute to its widespread adoption. InnoDB, its default storage engine, ensures Atomicity, Consistency, Isolation, and Durability (ACID), which are vital for data integrity and defined as follows:

• Atomicity means transactions are all-or-nothing.
• Consistency ensures data moves from one valid state to another.
• Isolation keeps concurrent transactions from interfering.
• Durability makes committed changes permanent.

However, this single-instance reliability often creates an expectation that ACID properties will seamlessly scale. As data volumes and application complexity grow, MySQL’s traditional single-node architecture struggles to deliver strong consistency, high availability, and horizontal scalability simultaneously. 

This blog explores why distributed SQL is the next logical evolution from MySQL for enterprises that need to uphold ACID properties at scale, with a gentle introduction to TiDB as a compelling alternative.

The Limitations of MySQL for ACID at Scale

While developers love MySQL for its simplicity, ubiquity, strong single-instance transactional guarantees, and mature ecosystem, scaling it for data-intensive, demanding applications reveals significant bottlenecks.

The Scaling Bottlenecks

Vertically scaling MySQL (i.e., adding more resources to a single server) offers diminishing returns and rapidly increasing costs. Doubling resources might only yield a minor performance boost, making it an inefficient long-term strategy.

Primary-secondary replication, used for read scalability, introduces challenges like replication lag, where secondary nodes fall behind the primary, leading to stale reads. Data inconsistencies can also arise between primary and secondary nodes, especially with certain binary log formats or during failover. Manual failover processes are often complex, time-consuming, and risk data loss if not perfectly executed.

Manual sharding, an attempt to scale writes by partitioning data across multiple MySQL instances, introduces immense complexity. Choosing a sharding key is difficult and can lead to hotspots. Applications become shard-aware, increasing development overhead. Cross-shard queries are inefficient, and maintaining ACID across shards requires complex application-level logic. Rebalancing data and managing schema changes across shards are also significant operational pains. This complexity impacts developer productivity and increases the total cost of ownership.

The ACID Trade-offs in a Distributed World

The CAP theorem states that a distributed system can only simultaneously guarantee two of three properties: Consistency, Availability, and Partition Tolerance. Since network partitions (P) are inevitable in distributed systems, a choice must be made between Consistency (C) and Availability (A). MySQL, in distributed configurations, often prioritizes Consistency, becoming a CP system, which can mean sacrificing availability during partitions.

It’s important to distinguish ACID “Consistency” (database internal validity) from CAP “Consistency” (all nodes see the same data). When applications scale globally, the strong, single-node ACID guarantees of MySQL become difficult to maintain across a distributed setup without significant compromises or complexities.

What is Distributed SQL?

Distributed SQL databases merge the relational strengths of SQL with the scalability of NoSQL. They appear as a single logical database but operate across a cluster of servers, automatically distributing and replicating data.

Core Concepts

Key characteristics include:

• Distributed Transactions: ACID-compliant transactions that can span multiple nodes, often using protocols like Two-Phase Commit (2PC).
• Strong Consistency with Horizontal Scalability: Maintaining data consistency (often serializable isolation) while scaling out by adding more nodes.
• Distributed Deployments: Spanning multiple data centers or regions for low latency access and high availability, often using consensus protocols like Raft or Paxos for data replication and consistency.

Distributed SQL vs. Traditional RDBMS vs. NoSQL

Feature	Traditional RDBMS	NoSQL	Distributed SQL
Data Model	Relational (Structured)	Document, Key-Value, etc. (Flexible Schema)	Relational (Structured)
Scalability	Vertical, Manual Sharding	Horizontal	Horizontal (Often Automatic)
Consistency	Strong (Single Instance)	Often Eventual (Tunable)	Strong (Distributed)
Transactions	Strong ACID (Single Instance)	Varies (Often limited or BASE)	Strong ACID (Distributed)
SQL Support	Yes	Limited or NoSQL query languages	Yes (Often MySQL or PostgreSQL compatible)
Use Cases	Traditional OLTP, Web Apps	Big Data, Real-time Apps, IoT	Scalable OLTP, Operational Insights, Global Apps

Distributed SQL aims to provide the best of both worlds: the familiar SQL and ACID guarantees of relational databases, plus the horizontal scalability and resilience of NoSQL systems.

Why MySQL Needs a Distributed SQL Alternative

For many data-intensive applications, MySQL’s limitations become critical operational pain points.

Real-world Use Cases Where MySQL Falls Short

• Global Financial Applications: Require multi-region strong consistency, which is hard to achieve with traditional MySQL replication.
• E-commerce Platforms: Need high availability during peak loads and sales events, where MySQL failover can be slow and risky.
• SaaS Platforms: Scaling from single-region to multi-cloud or multi-region deployments with MySQL is operationally complex and costly.

Operational Pain Points

• Manual Failovers and Downtime: MySQL replication often requires manual intervention for failovers, leading to downtime.
• Data Inconsistency: Replication lag can cause data drift between the primary and replicas.
• Sharding Complexity: Manual sharding increases development and operational burdens, impacting productivity and TCO.

Distributed SQL: How It Solves the ACID Problem at Scale

Distributed SQL databases are architected to overcome these limitations natively.

• Built-in Horizontal Scalability: These systems feature automatic data sharding and rebalancing, allowing seamless scaling by adding nodes without application rewrites or manual intervention.
• Strong Consistency and High Availability: Consensus protocols like Raft or Paxos ensure data is consistently replicated across multiple nodes (and often regions). These protocols provide strong ACID guarantees and automatic failover in case of node or even regional failures.
• Operational Simplicity: These systems present a unified SQL layer to the application, abstracting the distributed complexity. Failovers, backups, and scaling workflows are often automated and simplified.

Introducing TiDB: Distributed SQL for MySQL Users

TiDB is an open-source, MySQL-compatible Distributed SQL database designed for horizontal scalability, strong consistency, and high availability. It aims to be a one-stop solution for scaling Online Transactional Processing (OLTP) workloads while also performing real-time analytics on operational data.

Key Features for Scaling ACID Workloads

• Mixed Workload Support: TiDB integrates row storage and columnar storage, allowing real-time analytics on fresh transactional data.
• Strong Consistency: Achieved via the Raft consensus algorithm within its distributed key-value storage layer, ensuring ACID compliance across the cluster.
• Elastic Scaling: Scales horizontally by adding nodes, with automatic data sharding (into “Regions”) and rebalancing, eliminating manual sharding pain.
• Multi-Cloud and Hybrid Cloud Ready: Deployable on-premises, in public clouds (AWS, Google Cloud), or hybrid environments.

Why TiDB is a Natural Evolution for MySQL Users Who Need ACID at Scale

TiDB’s high compatibility with the MySQL protocol (including MySQL 5.7 and 8.0 syntax) means many existing applications, client libraries, and tools (like PHPMyAdmin, Navicat, MySQL Workbench) can be used with minimal or no code changes. Developers get a familiar SQL interface but with the power of distributed scalability and resilience.

Success Stories and Real-World Adoption

Companies across various sectors have replaced complex MySQL sharding with TiDB.

• E-commerce: Flipkart simplified its Coin Manager rewards platform, improving reliability and handling data growth effortlessly. ZaloPay, a mobile payment app, uses TiDB for its merchant platform to serve millions. Shopee leverages TiDB for log storage and its chat system, simplifying scaling.
• FinTech: SB Payment Service adopted TiDB for a new online payment system, citing better performance and reduced downtime.
• SaaS: Various SaaS companies have migrated from MySQL (RDS, Aurora, InnoDB Cluster) to TiDB to overcome scalability bottlenecks and reduce costs.

A Migration Path: From MySQL to ACID at Scale

Migrating from MySQL to a distributed SQL database like TiDB can be a smooth process.

Application Compatibility: SQL Layer Matters

TiDB’s MySQL compatibility ensures that the developer experience remains largely consistent. PingCAP provides a suite of tools to aid migration, including TiDB Data Migration (DM) for full and incremental replication, TiDB Dumpling for data export, TiDB Lightning for fast bulk imports, and sync-diff-inspector for data validation.

Best Practices for Migration

Strategies like phased migrations and hybrid deployments can minimize risk and downtime. Thorough planning involves addressing potential incompatibilities (e.g., TiDB’s handling of auto-increment IDs, absence of foreign key enforcement at the DB layer by default) and comprehensive testing. Tools like TiCDC facilitate continuous data replication, enabling near zero-downtime migrations.

Conclusion

MySQL’s legacy is undeniable, offering simplicity and reliability for countless applications. However, the demands of data-intensive, large-scale applications often push MySQL beyond its architectural limits, especially when strong ACID guarantees are non-negotiable. The complexities of manual sharding, replication lag, and difficult failovers highlight the need for a more evolved solution.

Distributed SQL databases represent this evolution. They are designed from the ground up to provide horizontal scalability, strong consistency, and high availability without the operational pain points of traditional scaled MySQL.

For organizations rooted in the MySQL ecosystem, TiDB offers a compelling and natural progression. Its MySQL compatibility minimizes migration friction, while its distributed architecture delivers the scalability and resilience required for today’s data-intensive world. With features like mixed workload processing, automatic sharding, and robust ACID transactions, TiDB empowers businesses to grow without being constrained by their database. This makes it the go-to distributed SQL solution for MySQL users seeking scale, consistency, and operational simplicity.

Want to dive deeper into how MySQL compares to distributed SQL? Watch our on-demand webinar for even more insights, use cases, and migration strategies.